Agent Skills Hub

jules-skill

Manage Jules (Google's async AI coding agent) directly from your terminal. Create, monitor, and interact with Jules coding sessions, approve plans, and handle feedback loops across repositories.

claude-api

Expert guidance for Claude Messages API: structured outputs, prompt caching, tool use, and migration from deprecated Claude 3.x models to 4.5. Prevents common API errors.

memory-systems

Guides agent memory system implementation, compares frameworks (Mem0, Zep, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention.

create-unit-test

Create and run unit tests for AnySoftKeyboard following project architecture guidelines (Robolectric, naming, location).

proofread

Automated, non-destructive proofreading for LaTeX and Quarto lecture files, generating quality reports for grammar, typos, and academic style.

home-assistant-master

Home Assistant OS (HAOS) operations skill for agents. Features read-only diagnostics, automation design, health auditing, and safety-first configuration management.

skill-authoring-workflow

A standardized workflow for converting raw PM notes, workshops, or rough drafts into polished, validated, and repository-compliant AI skills.

strategy-scaling-architecture

Architectural planning and scaling for spectre-build, covering GUI, server layers, multi-model support, and industrial pipeline orchestration.

using-superpowers

The foundational skill for the Superpowers methodology. Ensures agents correctly identify and invoke required development skills before starting any task or conversation.

open-source-maintainer

End-to-end GitHub repository maintenance agent. Automates triage, PR review, issue analysis, and maintenance reporting to ensure long-term repository health, stability, and growth.

aarnphm.github.io

A highly customized personal garden based on Quartz v4, featuring enhanced Markdown parsing, telescopic text, TikZ/pseudocode rendering, and Obsidian integration.

rag-implementation

Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.